Boundedness of stochastic cellular neural networks with delays

被引：0
|
作者：
Zhou, Qinghua [1 ]
机构：
[1] Department of Mathematics, Zhaoqing University, Zhaoqing 526061, China
来源：
Journal of Information and Computational Science | 2012年 / 9卷 / 15期
关键词：
Stochastic systems - Cellular neural networks - Dynamical systems - Asymptotic stability;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The ultimate boundedness is one of foundational concepts, which plays an important role in investigating the global asymptotic stability, its control and synchronization for dynamical systems. The ultimate boundedness of stochastic cellular neural networks with time-varying delays is investigated. By employing Lyapunov method and matrix technique, some novel results and criteria on stochastic ultimate boundedness are derived. Finally, a numerical example is given to illustrate the correctness and effectiveness of our theoretical results. © 2012 by Binary Information Press.
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页码：4287 / 4294
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